定位系統目前廣泛應用於工程、醫療與個人定位等民生用途，常見的GPS(Global Positioning System)定位系統並不適用於室內環境，因此近年來發展適用於室內環境的無線網路定位系統，可採用接收訊號強度RSS(Received Signal Strength)的定位模式，但受限於RSS變動的特性導致定位誤差無法降低。本研究為降低RSS的定位誤差，先分析RSS訊號特性，瞭解RSS易受到環境與硬體限制因素所影響，其中環境因素主要包含多路徑效應、遮蔽效應與衰退效應，而硬體限制因素包含發送端與接收端之差異及天線指向增益不均勻。本研究使用移動平均濾波器與高斯濾波器來抑制RSS訊號雜訊，利用實驗的方式與最佳化的觀念來建立路徑衰減模型，再透過環境特徵比對法與三角定位法來定位。並整合SOPC(System on Programmable Chip )與無線感測網路模組，發展出行動節點，進行靜態與動態的定位追蹤任務來驗證系統可行性。實驗結果顯示環境特徵比對法的精確度優於三角定位法，可獲得1公尺以內的平均誤差，並適用於行動節點之路徑追蹤。本研究可實際應用於室內定位，如物流追蹤與人員監控等各層面，未來將結合無線感測網路以提供多樣化定位資訊與服務。

Location techniques are essential for many engineering, medical and personal application. Due to attenuations and blockage, GPS (Global Positioning System) is not suitable in an indoor environment. Several indoor positioning techniques have been developed in recent years. This thesis is attempted to use a wireless sensor network module to investigate issues of received signal strength (RSS) based indoor geolocation.
In order to reduce the position error in RSS, we first analyzed the characteristic of RSS. RSS measurements are subject to environment factor, including multi-path, fading and shadowing of RF-channel, as well as hardware factor, such as transmitter and receiver variability and antenna radiation pattern. The present study applies the moving average filter and Gaussian filter to process of RSS. Measurements and an optimization technique are adopted to build the path loss model. To assess the performance through experiments a mobile node is developed base on the integration of SOPC (System on Programmable Chip) and wireless sensor network modules. Finally, the experiments were conducted to verify the indoor positioning algorithm and to track the trajectory of the mobile node.
The results show that the fingerprinting method is more accurate than the triangulation method in general. This successfully reduced the mean squared error in static localization to be within one meter, and the trajectory of the mobile node was also successfully tracked.

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